Feasibility of using machine learning on insurance claims to identify correlates of lower extremity amputation in insured adults with type 2 diabetes who initiate treatment with sodium-glucose co-transporter 2 (SGLT-2) inhibitors

Yuan Luo, Andrew J. Cooper, Raymond Kang, Ronald Ackermann. Feasibility of using machine learning on insurance claims to identify correlates of lower extremity amputation in insured adults with type 2 diabetes who initiate treatment with sodium-glucose co-transporter 2 (SGLT-2) inhibitors. In AMIA 2021, American Medical Informatics Association Annual Symposium, San Diego, CA, USA, October 30, 2021 - November 3, 2021. AMIA, 2021. [doi]

@inproceedings{LuoCKA21,
  title = {Feasibility of using machine learning on insurance claims to identify correlates of lower extremity amputation in insured adults with type 2 diabetes who initiate treatment with sodium-glucose co-transporter 2 (SGLT-2) inhibitors},
  author = {Yuan Luo and Andrew J. Cooper and Raymond Kang and Ronald Ackermann},
  year = {2021},
  url = {https://knowledge.amia.org/74229-amia-1.4622266/t004-1.4626008/t004-1.4626009/3575466-1.4626214/3577505-1.4626211},
  researchr = {https://researchr.org/publication/LuoCKA21},
  cites = {0},
  citedby = {0},
  booktitle = {AMIA 2021, American Medical Informatics Association Annual Symposium, San Diego, CA, USA, October 30, 2021 - November 3, 2021},
  publisher = {AMIA},
}